8,106 research outputs found
Two-Restricted One Context Unification is in Polynomial Time
One Context Unification (1CU) extends first-order unification by introducing a single context variable. This problem was recently shown to be in NP, but it is not known to be solvable in polynomial time. We show that the case of 1CU where the context variable occurs at most twice in the input (1CU2r) is solvable in polynomial time. Moreover, a polynomial representation of all solutions can also be computed in polynomial time. The 1CU2r problem is important as it is used as a subroutine in polynomial time algorithms for several more-general classes of 1CU problem. Our algorithm can be seen as an extension of the usual rules of first-order unification and can be used to solve related problems in polynomial time, such as first-order unification of two terms that tolerates one clash. All our results assume that the input terms are represented as Directed Acyclic Graphs
Unification and Matching on Compressed Terms
Term unification plays an important role in many areas of computer science,
especially in those related to logic. The universal mechanism of grammar-based
compression for terms, in particular the so-called Singleton Tree Grammars
(STG), have recently drawn considerable attention. Using STGs, terms of
exponential size and height can be represented in linear space. Furthermore,
the term representation by directed acyclic graphs (dags) can be efficiently
simulated. The present paper is the result of an investigation on term
unification and matching when the terms given as input are represented using
different compression mechanisms for terms such as dags and Singleton Tree
Grammars. We describe a polynomial time algorithm for context matching with
dags, when the number of different context variables is fixed for the problem.
For the same problem, NP-completeness is obtained when the terms are
represented using the more general formalism of Singleton Tree Grammars. For
first-order unification and matching polynomial time algorithms are presented,
each of them improving previous results for those problems.Comment: This paper is posted at the Computing Research Repository (CoRR) as
part of the process of submission to the journal ACM Transactions on
Computational Logic (TOCL)
On Unification Modulo One-Sided Distributivity: Algorithms, Variants and Asymmetry
An algorithm for unification modulo one-sided distributivity is an early
result by Tid\'en and Arnborg. More recently this theory has been of interest
in cryptographic protocol analysis due to the fact that many cryptographic
operators satisfy this property. Unfortunately the algorithm presented in the
paper, although correct, has recently been shown not to be polynomial time
bounded as claimed. In addition, for some instances, there exist most general
unifiers that are exponentially large with respect to the input size. In this
paper we first present a new polynomial time algorithm that solves the decision
problem for a non-trivial subcase, based on a typed theory, of unification
modulo one-sided distributivity. Next we present a new polynomial algorithm
that solves the decision problem for unification modulo one-sided
distributivity. A construction, employing string compression, is used to
achieve the polynomial bound. Lastly, we examine the one-sided distributivity
problem in the new asymmetric unification paradigm. We give the first
asymmetric unification algorithm for one-sided distributivity
The Algebraic Intersection Type Unification Problem
The algebraic intersection type unification problem is an important component
in proof search related to several natural decision problems in intersection
type systems. It is unknown and remains open whether the algebraic intersection
type unification problem is decidable. We give the first nontrivial lower bound
for the problem by showing (our main result) that it is exponential time hard.
Furthermore, we show that this holds even under rank 1 solutions (substitutions
whose codomains are restricted to contain rank 1 types). In addition, we
provide a fixed-parameter intractability result for intersection type matching
(one-sided unification), which is known to be NP-complete.
We place the algebraic intersection type unification problem in the context
of unification theory. The equational theory of intersection types can be
presented as an algebraic theory with an ACI (associative, commutative, and
idempotent) operator (intersection type) combined with distributivity
properties with respect to a second operator (function type). Although the
problem is algebraically natural and interesting, it appears to occupy a
hitherto unstudied place in the theory of unification, and our investigation of
the problem suggests that new methods are required to understand the problem.
Thus, for the lower bound proof, we were not able to reduce from known results
in ACI-unification theory and use game-theoretic methods for two-player tiling
games
Memoization for Unary Logic Programming: Characterizing PTIME
We give a characterization of deterministic polynomial time computation based
on an algebraic structure called the resolution semiring, whose elements can be
understood as logic programs or sets of rewriting rules over first-order terms.
More precisely, we study the restriction of this framework to terms (and logic
programs, rewriting rules) using only unary symbols. We prove it is complete
for polynomial time computation, using an encoding of pushdown automata. We
then introduce an algebraic counterpart of the memoization technique in order
to show its PTIME soundness. We finally relate our approach and complexity
results to complexity of logic programming. As an application of our
techniques, we show a PTIME-completeness result for a class of logic
programming queries which use only unary function symbols.Comment: Soumis {\`a} LICS 201
Light Logics and the Call-by-Value Lambda Calculus
The so-called light logics have been introduced as logical systems enjoying
quite remarkable normalization properties. Designing a type assignment system
for pure lambda calculus from these logics, however, is problematic. In this
paper we show that shifting from usual call-by-name to call-by-value lambda
calculus allows regaining strong connections with the underlying logic. This
will be done in the context of Elementary Affine Logic (EAL), designing a type
system in natural deduction style assigning EAL formulae to lambda terms.Comment: 28 page
Context unification is in PSPACE
Contexts are terms with one `hole', i.e. a place in which we can substitute
an argument. In context unification we are given an equation over terms with
variables representing contexts and ask about the satisfiability of this
equation. Context unification is a natural subvariant of second-order
unification, which is undecidable, and a generalization of word equations,
which are decidable, at the same time. It is the unique problem between those
two whose decidability is uncertain (for already almost two decades). In this
paper we show that the context unification is in PSPACE. The result holds under
a (usual) assumption that the first-order signature is finite.
This result is obtained by an extension of the recompression technique,
recently developed by the author and used in particular to obtain a new PSPACE
algorithm for satisfiability of word equations, to context unification. The
recompression is based on performing simple compression rules (replacing pairs
of neighbouring function symbols), which are (conceptually) applied on the
solution of the context equation and modifying the equation in a way so that
such compression steps can be in fact performed directly on the equation,
without the knowledge of the actual solution.Comment: 27 pages, submitted, small notation changes and small improvements
over the previous tex
Data-Oriented Language Processing. An Overview
During the last few years, a new approach to language processing has started
to emerge, which has become known under various labels such as "data-oriented
parsing", "corpus-based interpretation", and "tree-bank grammar" (cf. van den
Berg et al. 1994; Bod 1992-96; Bod et al. 1996a/b; Bonnema 1996; Charniak
1996a/b; Goodman 1996; Kaplan 1996; Rajman 1995a/b; Scha 1990-92; Sekine &
Grishman 1995; Sima'an et al. 1994; Sima'an 1995-96; Tugwell 1995). This
approach, which we will call "data-oriented processing" or "DOP", embodies the
assumption that human language perception and production works with
representations of concrete past language experiences, rather than with
abstract linguistic rules. The models that instantiate this approach therefore
maintain large corpora of linguistic representations of previously occurring
utterances. When processing a new input utterance, analyses of this utterance
are constructed by combining fragments from the corpus; the
occurrence-frequencies of the fragments are used to estimate which analysis is
the most probable one.
In this paper we give an in-depth discussion of a data-oriented processing
model which employs a corpus of labelled phrase-structure trees. Then we review
some other models that instantiate the DOP approach. Many of these models also
employ labelled phrase-structure trees, but use different criteria for
extracting fragments from the corpus or employ different disambiguation
strategies (Bod 1996b; Charniak 1996a/b; Goodman 1996; Rajman 1995a/b; Sekine &
Grishman 1995; Sima'an 1995-96); other models use richer formalisms for their
corpus annotations (van den Berg et al. 1994; Bod et al., 1996a/b; Bonnema
1996; Kaplan 1996; Tugwell 1995).Comment: 34 pages, Postscrip
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